GM模型的几何性质及统计检验

以空间向量几何理论为基础，详细地分析了Ｇａｕｓｓ－Ｍａｒｋｏｖ线性模型的几何性质；在实现了模型图形化描述的基础上，利用各解向量的几何及统计性质构造出了不同情形下的统计检验方法和相应的检验统计量，为全面、深入地研究和灵活运用该模型提出了一种简洁直观的数学方法     

反求工程的产品几何建模技术研究

分析了目前在反求工程产品几何建模中广泛应用的曲面模型的局限性，指出反求工程为实现创新功能必须采用产品特征模型，提出了基于实体造型的特征建模方法。这种方法可以避免曲面模型的缺陷，拓宽反求工程的应用范围，是实现三维重构的新方法。探讨了有关的理论和关键技术。     

基于特征的多模式CAPP系统的研究

构造了一种实用化的CAPP系统框架。该系统提供了检索式工艺生成，基于工艺模板的工艺生成，基于特征匹配的工艺生成，这三种决策方式功能并列在CAPP系统中，是相互关联的，较好地解决了CAPP系统的实用性和通用性问题。     

逆向工程中的一种编号点及其识别方法

对机械逆向工程中运用到的一种点的编码方式进行了简单的阐述和特征化，并详细介绍了运用区域搜索进行目标分割以及运用查找特性表并结合矩不变量的一种识别的算法。     

等离子熔积直接成形形状特性的基础研究

系统分析了熔积成形技术中影响成形形状特性的原因,研究了转移弧电流、扫描速度和起弧高度对成形精度的影响机理.实验表明,以上参数对等离子熔积直接成形形状特性的影响显著,对改善零件的成形精度起决定性的作用;通过优化成形工艺参数,焊道表面质量得到显著好转.     

CF均布型炉箅的开发与应用

介绍了固定层间歇式煤气炉炉箅设计开发指导思想与CF均布型炉箅结构特点及应用情况。     

Discourse cues to deception in the case of multiple receivers

Behavioral cues to deception are instrumental in detecting deception. As one of the primary sources of deception behavior, text has been analyzed at the level of sub-sentence or message but not the discourse of interaction. Additionally, empirical studies on cues to deception in the case of multiple receivers remain nonexistent. To fill these voids, we propose a discourse framework and six hypotheses about deception behaviors in a multi-receiver environment. The deception behaviors are operationalized by discourse features based on an analysis of real-world data. The results of statistical analysis validate the efficacy of discourse features in discriminating deceivers from truth-tellers.     

双组分环氧胶粘剂在我厂的应用

简单介绍了双组分环氧胶粘剂的特点、组成及固化反应机理 ,并且详细叙述了我厂双组分环氧胶粘剂的组分、配制工艺和灌胶工艺以及讨论了双组分环氧胶粘剂在我厂的应用情况 ,为我厂的军品及民用电器产品的灌封胶接提供了广泛的前景     

Computer aided detection system for micro calcifications in digital mammograms

Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. Mammogram breast X-ray is considered the most reliable method in early detection of breast cancer. However, it is difficult for radiologists to provide both accurate and uniform evaluation for the enormous mammograms generated in widespread screening. Micro calcification clusters (MCCs) and masses are the two most important signs for the breast cancer, and their automated detection is very valuable for early breast cancer diagnosis. The main objective is to discuss the computer-aided detection system that has been proposed to assist the radiologists in detecting the specific abnormalities and improving the diagnostic accuracy in making the diagnostic decisions by applying techniques splits into three-steps procedure beginning with enhancement by using Histogram equalization (HE) and Morphological Enhancement, followed by segmentation based on Otsu's threshold the region of interest for the identification of micro calcifications and mass lesions, and at last classification stage, which classify between normal and micro calcifications ‘patterns and then classify between benign and malignant micro calcifications. In classification stage; three methods were used, the voting K-Nearest Neighbor classifier (K-NN) with prediction accuracy of 73%, Support Vector Machine classifier (SVM) with prediction accuracy of 83%, and Artificial Neural Network classifier (ANN) with prediction accuracy of 77%.